Abstract: An improved search engine creates correlations linking terms from inputs provided by a user to selected target terms. The correlation search process receives pre-processed inputs from a user including a wide variety of input formats including keywords, phrases, sentences, concepts, compound queries, complex queries and orthogonal queries. The pre-processing also includes pre-processing of general digital information objects and static or dynamic generation of questions. After a correlation search of the information presented by the pre-processing, the search results are processed in novel ways to provide an improved relevance ranking of results.

Abstract: Techniques for identifying knowledge use an graphical user interface for inputting one or more terms to be explored for additional knowledge. Then a search is conducted across one or more sources of information to identify resources containing information about or information associated with said terms. The resources are decomposed into elemental units of information and stored in a data structures called nodes. A group of nodes are stored in a node pool and, from the node pool, correlations of nodes are constructed that represent knowledge.

Abstract: An improved search engine creates correlations linking terms from inputs provided by a user to selected target terms. The correlation search process receives pre-processed inputs from a user including a wide variety of input formats including keywords, phrases, sentences, concepts, compound queries, complex queries and orthogonal queries. The pre-processing also includes pre-processing of general digital information objects and static or dynamic generation of questions. After a correlation search of the information presented by the pre-processing, the search results are processed in novel ways to provide an improved relevance ranking of results.

Abstract: Techniques for identifying knowledge use a graphical user interface for inputting one or more terms to be explored for additional knowledge. Then a search is conducted across one or more sources of information to identify resources containing information about or information associated with said terms. The resources are decomposed into elemental units of information and stored in a data structures called nodes. A group of nodes are stored in a node pool and, from the node pool, correlations of nodes are constructed that represent knowledge using information about relation types. Information about relations types is determined using a relation classifier.

Abstract: Techniques for identifying knowledge use an graphical user interface for inputting one or more terms to be explored for additional knowledge. Then a search is conducted across one or more sources of information to identify resources containing information about or information associated with said terms. The resources are decomposed into elemental units of information and stored in a data structures called nodes. A group of nodes are stored in a node pool and, from the node pool, correlations of nodes are constructed that represent knowledge.

Abstract: Text is extracted from and information resource such as documents, emails, relational database tables and other digitized information sources. The extracted text is processed using a decomposition function to create. Nodes are a particular data structure that stores elemental units of information. The nodes can convey meaning because they relate a subject term or phrase to an attribute term or phrase. Removed from the node data structure, the node contents are or can become a text fragment which conveys meaning, i.e., a note. The notes generated from each digital resource are associated with the digital resource from which they are captured. The notes are then stored, organized and presented in several ways which facilitate knowledge acquisition and utilization by a user.

Abstract: An improved search engine creates correlations linking terms from inputs provided by a user to selected target terms. The correlation search process receives pre-processed inputs from a user including a wide variety of input formats including keywords, phrases, sentences, concepts, compound queries, complex queries and orthogonal queries. The pre-processing also includes pre-processing of general digital information objects and static or dynamic generation of questions. After a correlation search of the information presented by the pre-processing, the search results are processed in novel ways to provide an improved relevance ranking of results.

Abstract: An improved search engine creates correlations linking terms from inputs provided by a user to selected target terms. The correlation search process receives pre-processed inputs from a user including a wide variety of input formats including keywords, phrases, sentences, concepts, compound queries, complex queries and orthogonal queries. The pre-processing also includes pre-processing of general digital information objects and static or dynamic generation of questions. After a correlation search of the information presented by the pre-processing, the search results are processed in novel ways to provide an improved relevance ranking of results.

Abstract: A method for processing textual resources may include decomposing the textual resources into a sequence of textual fragments, and searching the sequence of textual fragments for a match to a relational pattern including first and second tokens, and a word based relational bond therebetween. The searching may include searching each textual fragment of the sequence of textual fragments for a match to the word based relational bond, and when a given textual fragment matches the word based relational bond, determining whether the given textual fragment also matches the first and second tokens. The method may include when the given textual fragment also matches the first and second tokens, generating a node having the first and second tokens and the word based relational bond therebetween, and storing the node in a node pool.

Abstract: An improved search engine creates correlations linking terms from inputs provided by a user to selected target terms. The correlation search process receives pre-processed inputs from a user including a wide variety of input formats including keywords, phrases, sentences, concepts, compound queries, complex queries and orthogonal queries. The pre-processing also includes pre-processing of general digital information objects and static or dynamic generation of questions. After a correlation search of the information presented by the pre-processing, the search results are processed in novel ways to provide an improved relevance ranking of results.

Abstract: Techniques for identifying knowledge use a graphical user interface for inputting one or more terms to be explored for additional knowledge. Then a search is conducted across one or more sources of information to identify resources containing information about or information associated with said terms. The resources are decomposed into elemental units of information and stored in a data structures called nodes. A group of nodes are stored in a node pool and, from the node pool, correlations of nodes are constructed that represent knowledge using information about relation types. Information about relations types is determined using a relation classifier.

Abstract: Techniques for identifying knowledge use an graphical user interface for inputting one or more terms to be explored for additional knowledge. Then a search is conducted across one or more sources of information to identify resources containing information about or information associated with said terms. The resources are decomposed into elemental units of information and stored in a data structures called nodes. A group of nodes are stored in a node pool and, from the node pool, correlations of nodes are constructed that represent knowledge.

Abstract: An improved search engine creates correlations linking terms from inputs provided by a user to selected target terms. The correlation search process receives pre-processed inputs from a user including a wide variety of input formats including keywords, phrases, sentences, concepts, compound queries, complex queries and orthogonal queries. The pre-processing also includes pre-processing of general digital information objects and static or dynamic generation of questions. After a correlation search of the information presented by the pre-processing, the search results are processed in novel ways to provide an improved relevance ranking of results.

Abstract: Techniques for identifying knowledge use a graphical user interface for inputting one or more terms to be explored for additional knowledge. Then a search is conducted across one or more sources of information to identify resources containing information about or information associated with said terms. The resources are decomposed into elemental units of information and stored in a data structures called nodes. A group of nodes are stored in a node pool and, from the node pool, correlations of nodes are constructed that represent knowledge using information about relation types. Information about relations types is determined using a relation classifier.

Abstract: Techniques for identifying knowledge use an graphical user interface for inputting one or more terms to be explored for additional knowledge. Then a search is conducted across one or more sources of information to identify resources containing information about or information associated with said terms. The resources are decomposed into elemental units of information and stored in a data structures called nodes. A group of nodes are stored in a node pool and, from the node pool, correlations of nodes are constructed that represent knowledge.

Abstract: Text is extracted from and information resource such as documents, emails, relational database tables and other digitized information sources. The extracted text is processed using a decomposition function to create. Nodes are a particular data structure that stores elemental units of information. The nodes can convey meaning because they relate a subject term or phrase to an attribute term or phrase. Removed from the node data structure, the node contents are or can become a text fragment which conveys meaning, i.e., a note. The notes generated from each digital resource are associated with the digital resource from which they are captured. The notes are then stored, organized and presented in several ways which facilitate knowledge acquisition and utilization by a user.

Abstract: Text is extracted from and information resource such as documents, emails, relational database tables and other digitized information sources. The extracted text is processed using a decomposition function to create. Nodes are a particular data structure that stores elemental units of information. The nodes can convey meaning because they relate a subject term or phrase to an attribute term or phrase. Removed from the node data structure, the node contents are or can become a text fragment which conveys meaning, i.e., a note. The notes generated from each digital resource are associated with the digital resource from which they are captured. The notes are then stored, organized and presented in several ways which facilitate knowledge acquisition and utilization by a user.